Applications of Colorimeter in Machine Visions for Checking Printed-Circuit Boards
Main Article Content
Abstract
Application of colorimetry in color identification for checking printed-circuit boards (PCBs) is proposed. Inspection of electronic components during the assembly of the printed circuit boards (PCBs) can be done by an analysis of color image. This method significantly enchances the imahe-processing speed. Additionally, the inspection accuracy can be attained by the use of color isodiscrimination contour criterio.
Keywords: colorimetry, machine vision, automated visual inspections, isodiscrimination contour, and color identification
Corresponding author: E-mail: cast@kmitl.ac.th
Article Details
Copyright Agreement Statement
The corresponding author has to submit Copyright Agreement form after the article is accepted for publication in order to warrant that this contribution is original and that he/she has full power to make this grant. The author signs for and accepts responsibility for releasing this material on behalf of any and all co-authors.
The author(s) grant Current Applied Science and Technology a non-exclusive, irrevocable, royalty-free license to publish, reproduce, distribute, and archive the article in print and electronic form with effect if and when the article is accepted for publication. In the event that the article is withdrawn prior to acceptance or is declined, this agreement shall have no effect, and no party shall be bound by it.
The author(s) retain copyright of this article, including but not limited to the right to reproduce and distribute the article, to include it in a thesis or book, and to post it on an institutional or personal repository, provided that the original publication in Current Applied Science and Technology is properly cited.
References
[2] D. Mital, et al. Color Vision for Industrial Applications IEEE: IECON’90: 548-551, 1990.
[3] P. Tantaswadi, et al. Machine Vision for Automated Visual Inspection of Cotton Quality in Textile Industries using Color Isodiscrimination Contour, Comp. & Indust. Engr., 37, 1999, pp. 347-350.
[4] C. Gunawardena, et al. A Spot-type Defect Detection and Color Identification System for Agriculture Produce. IEEE: IECON’91: 2531-2534, 1991.
[5] D. H. Brainard, Handbook of Optics: Volume II, OSA.
[6] G.D. Asensi, et al. Automatic Color Identification System Through Computer Vision Techniques for its Application in Classification of Canned Vegetable Tins According to Product Sizes and Qualities. IEEE 1994.
[7] M.Zuhdan, et al. classifying Papers and Checking Similarity of Two Papers using Color Images. ACCV’95, Dec. 1995, Singapore.
[8] R. Crane, A simplified Approach to Image Processing, Prentice-Hall, Inc.